Intelligent Decision-Making for Smart Home Energy Management

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• 作者：Heider Berlink ; Nelson Kagan…
• 关键词：SmartHome ; SmartGrid ; Energy management system ; Reinforcement learning
• 刊名：Journal of Intelligent and Robotic Systems
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：80
• 期：1-supp
• 页码：331-354
• 全文大小：4,931 KB
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• 作者单位：Heider Berlink (1)
  Nelson Kagan (1)
  Anna Helena Reali Costa (1)
  
  1. Escola Politécnica, Universidade de São Paulo (USP), São Paulo, SP, Brazil
  
• 刊物类别：Engineering
• 刊物主题：Automation and Robotics
  Electronic and Computer Engineering
  Artificial Intelligence and Robotics
  Mechanical Engineering
  
• 出版者：Springer Netherlands
• ISSN：1573-0409

文摘

One of the goals of Smart Grids is to encourage distributed generation of energy in houses, hence allowing the user to profit by injecting energy into the power grid. The implementation of a differentiated tariff of energy per time of use, coupled with energy storage in batteries, enables profit maximization by the user, who can choose to sell or store the energy generated whenever it is convenient. This paper proposes a solution to the sequential decision-making problem of energy sale by applying reinforcement learning. Results show a significant increase in the total long-term profit by using the policy obtained with the proposed approach, when compared with a price-unaware selling policy.